Works Published in 2020

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Displaying works 1 - 20 of 21 in total

Sorted by most recent date added to the index first, which may not be the same as publication date order.

2020 article

EVALUATING DIABETIC RETINOPATHY SCREENING INTERVENTIONS IN A MICROSIMULATION MODEL

2020 WINTER SIMULATION CONFERENCE (WSC), pp. 944–955.

By: B. Swan n, S. Nambiar n, P. Koutouan n, M. Mayorga n, J. Ivy n & S. Fransen

TL;DR: A microsimulation integrating the natural history model of DR with a patient’s interaction with the care system increased adherence of patients with vision-threatening DR to follow-up eye care, decreased the number of ‘unnecessary’ visits in specialty eye care from patients without VTDR, and decreased the total years spent blind. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 30, 2021

2020 conference paper

A New Framework for Online Testing of Heterogeneous Treatment Effect

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 34(6), 10310–10317.

Event: Thirty-Fourth AAAI Conference on Artificial Intelligence at New York Hilton Midtown, New York, New York, USA on February 7-12, 2020

TL;DR: The proposed test, named sequential score test (SST), is able to control type I error under continuous monitoring and detect multi-dimensional heterogeneous treatment effects and provides an online p-value calculation for SST, making it convenient for continuous monitoring. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: April 18, 2021

2020 journal article

Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel

JCO CLINICAL CANCER INFORMATICS, 4, 529–538.

By: F. Diaz-Garelli*, R. Strowd*, V. Lawson*, M. Mayorga n, B. Wells*, T. Lycan*, U. Topaloglu*

MeSH headings : Data Accuracy; Electronic Health Records; Humans; Physicians; Surveys and Questionnaires; Workflow
TL;DR: Clinicians and researchers reusing oncologic data should consider such heterogeneity when conducting secondary analyses of EHR data, and the need for specific structured DX data recording varies across clinical workflows and may be dependent on clinical information needs. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: March 1, 2021

2020 journal article

Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

PLOS COMPUTATIONAL BIOLOGY, 16(12).

MeSH headings : Computer Simulation; Machine Learning; Neural Networks, Computer; Nonlinear Dynamics
TL;DR: BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). (via Semantic Scholar)
Source: Web Of Science
Added: January 4, 2021

2020 journal article

Deep learning-enabled analysis reveals distinct neuronal phenotypes induced by aging and cold-shock

BMC BIOLOGY, 18(1).

By: S. Saberi-Bosari n, K. Flores n & A. San-Miguel n

author keywords: Deep learning; Convolutional neural networks; Neurodegeneration; Neuronal beading; Aging; Machine learning; Phenotyping; C; elegans
MeSH headings : Aging / physiology; Animals; Caenorhabditis elegans / physiology; Cold-Shock Response / physiology; Deep Learning; Neurons / physiology; Phenotype
TL;DR: Deep learning is applied to perform quantitative image-based analysis of complex neurodegeneration patterns exhibited by the PVD neuron in C. elegans and revealed that distinct patterns of morphological alteration are induced by aging and cold-shock, suggesting different mechanisms at play. (via Semantic Scholar)
Source: Web Of Science
Added: October 26, 2020

2020 article

Lifelong Analysis of Key Aging Genes as Determinants of Lifespan in <it>C</it>. <it>elegans</it>

San Miguel, A., Ramirez, J., & Flores, K. (2020, April). FASEB JOURNAL, Vol. 34.

TL;DR: This work presents a system that enables in vivo tracking the endogenous spatiotemporal activity of key aging genes throughout C. elegans lifespan using an integrative experimental platform based on microfluidics, computer vision, and tagging of endogenous genes via CRISPR/Cas9 genetic engineering approaches. (via Semantic Scholar)
Source: Web Of Science
Added: October 12, 2020

2020 journal article

Learning Equations from Biological Data with Limited Time Samples

BULLETIN OF MATHEMATICAL BIOLOGY, 82(9).

By: J. Nardini n, J. Lagergren n, A. Hawkins-Daarud*, L. Curtin*, B. Morris*, E. Rutter*, K. Swanson*, K. Flores n

author keywords: Equation learning; Numerical differentiation; Sparse regression; Model selection; Partial differential equations; Parameter estimation; Population dynamics; Glioblastoma multiforme
MeSH headings : Computational Biology / methods; Glioblastoma; Humans; Learning; Mathematical Concepts; Models, Biological; Nonlinear Dynamics
TL;DR: This work presents an equation learning methodology comprised of data denoising, equation learning, model selection and post-processing steps that infers a dynamical systems model from noisy spatiotemporal data and highlights how these results are informative for data-driven modeling-based tumor invasion predictions. (via Semantic Scholar)
Source: Web Of Science
Added: September 28, 2020

2020 article

Statistical Inference for Online Decision Making: In a Contextual Bandit Setting

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, Vol. 7, pp. 1–16.

author keywords: Epsilon-greedy; Inverse propensity weighted estimator; Model misspecification; Online decision making; Statistical inference
TL;DR: Using the martingale central limit theorem, it is shown that the online ordinary least squares estimator of model parameters is asymptotically normal and the in-sample inverse propensity weighted value estimator is asylptotic normal. (via Semantic Scholar)
UN Sustainable Development Goal Categories
16. Peace, Justice and Strong Institutions (OpenAlex)
Source: ORCID
Added: September 23, 2020

2020 journal article

Ascertaining properties of weighting in the estimation of optimal treatment regimes under monotone missingness

STATISTICS IN MEDICINE, 39(25), 3503–3520.

author keywords: augmented inverse probability weighting; dynamic treatment regimes; monotonic coarseness; outcome weighted learning; Q-learning
MeSH headings : Computer Simulation; Humans; Models, Statistical; Precision Medicine; Probability
TL;DR: The application of inverse probability weighted estimating equations as an alternative to multiple imputation in the context of monotonic missingness applies to a broad class of estimators of an optimal treatment regime including both Q‐learning and a generalization of outcome weighted learning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 17, 2020

2020 review

Notice to comply: A systematic review of clinician compliance with guidelines surrounding acute hospital-based infection management

[Review of ]. AMERICAN JOURNAL OF INFECTION CONTROL, 48(8), 940–947.

author keywords: Guideline adherence; Practice patterns (physicians); Quality; Program evaluation; Professional practice gaps; Outcome and process assessment (health care)
MeSH headings : Hospitals; Humans; Outcome Assessment, Health Care; Quality Improvement
TL;DR: Multimodal interventions and quality improvement initiatives seem to produce the greatest improvement in compliance, but trends in other factors were inconsistent. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Sources: Web Of Science, ORCID
Added: August 10, 2020

2020 review

A tutorial review of mathematical techniques for quantifying tumor heterogeneity

[Review of ]. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 17(4), 3660–3709.

By: R. Everett*, K. Flores*, N. Henscheid, J. Lagergren*, K. Larripa, D. Li, J. Nardini*, P. Nguyen*, E. Pitman, E. Rutter*

author keywords: cancer heterogeneity; mathematical oncology; tumor growth; glioblastoma multiforme; virtual populations; nonlinear mixed effects; spatiotemporal data; Bayesian estimation; generative; adversarial networks; non-parametric estimation; variational autoencoders; machine learning
MeSH headings : Bayes Theorem; Humans; Machine Learning; Models, Theoretical; Neoplasms; Precision Medicine
TL;DR: Several techniques that can be used to aid the mathematical modeller in inferring and quantifying both sources of heterogeneity from patient data are reviewed, including virtual populations, nonlinear mixed effects modeling, non-parametric estimation, Bayesian techniques, and machine learning. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: August 3, 2020

2020 journal article

The potential impact of the Affordable Care Act and Medicaid expansion on reducing colorectal cancer screening disparities in African American males

PLOS ONE, 15(1).

By: W. Powell*, L. Frerichs*, R. Townsley n, M. Mayorga n, J. Richmond*, G. Corbie-Smith*, S. Wheeler*, K. Lich*

MeSH headings : Black or African American; Aged; Colorectal Neoplasms / diagnosis; Colorectal Neoplasms / economics; Early Detection of Cancer / economics; Early Detection of Cancer / ethics; Healthcare Disparities / economics; Healthcare Disparities / trends; Humans; Male; Medicaid / economics; Medicaid / trends; Middle Aged; North Carolina; Patient Protection and Affordable Care Act / economics; Patient Protection and Affordable Care Act / trends; Race Factors / economics; United States
TL;DR: The findings suggest policies that expanding affordable, quality healthcare coverage could have a demonstrable, cost-saving impact while reducing cancer disparities are suggested. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: June 22, 2020

2020 journal article

DHPA: Dynamic Human Preference Analytics Framework— A Case Study on Taxi Drivers' Learning Curve Analysis

ACM Transactions on Intelligent Systems and Technology, 11(1).

author keywords: Urban computing; inverse reinforcement learning; preference dynamics
TL;DR: This work inversely learns the taxi drivers’ preferences from data and characterize the dynamics of such preferences over time, and extracts two types of features to model the decision space of drivers and learns the preferences of drivers with respect to these features. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: June 15, 2020

2020 journal article

Prepositioning disaster relief supplies using robust optimization

IISE TRANSACTIONS, 52(10), 1122–1140.

By: G. Velasquez n, M. Mayorga n & O. Ozaltin n

Contributors: G. Velasquez n, M. Mayorga n & O. Özaltın n

author keywords: Humanitarian logistics; inventory prepositioning; disaster relief supply chains; robust optimization
TL;DR: A case study of the hurricane season in the Southeast US is used to gain insights on the effects of optimization criteria and critical model parameters to relief supply prepositioning strategy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action (OpenAlex)
Sources: Web Of Science, ORCID
Added: April 6, 2020

2020 journal article

Learning partial differential equations for biological transport models from noisy spatio-temporal data

By: J. Lagergren n, J. Nardini n, G. Michael Lavigne n, E. Rutter n & K. Flores n

author keywords: numerical differentiation; equation learning; sparse regression; partial differential equations; parameter estimation; biological transport
TL;DR: It is shown that the ANN methodology outperforms previous denoising methods, including finite differences and both local and global polynomial regression splines, in the ability to accurately approximate partial derivatives and learn the correct PDE model. (via Semantic Scholar)
Source: Web Of Science
Added: March 30, 2020

2020 journal article

Optimal influenza vaccine distribution with equity

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 283(2), 714–725.

By: S. Enayati* & O. Ozaltin n

Contributors: S. Enayati* & O. Özaltın n

author keywords: OR in health services; Vaccine distribution; Influenza; Equity
TL;DR: The proposed model’s ability to consider vaccine coverage inequity is demonstrated and a derivative-free optimization approach is discussed, as an alternative solution method which can consider various different objective functions and constraints. (via Semantic Scholar)
UN Sustainable Development Goal Categories
3. Good Health and Well-being (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID
Added: March 16, 2020

2020 article

Statistical Inference for High-Dimensional Models via Recursive Online-Score Estimation

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION.

author keywords: Confidence interval; Generalized linear models; Online estimation; Ultrahigh dimensions
TL;DR: A new estimation and valid inference method for single or low-dimensional regression coefficients in high-dimensional generalized linear models and it is proved the proposed CI is asymptotically narrower than the CIs constructed based on the desparsified Lasso estimator and the decorrelated score statistic. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: ORCID
Added: February 11, 2020

2020 book

Dynamic Treatment Regimes: Statistical Methods for Precision Medicine

In CRC Press.

By: A. Tsiatis, M. Davidian, E. Laber & S. Holloway

Event: at Boca Raton, FL

Sources: ORCID, NC State University Libraries
Added: January 23, 2020

2020 journal article

Doubly robust inference when combining probability and non-probability samples with high dimensional data

Journal of the Royal Statistical Society: Series B (Statistical Methodology), 1.

author keywords: Data integration; Double robustness; Generalizability; Penalized estimating equation; Variable selection
TL;DR: This work considers integrating a non-probability sample with a probability sample which provides high dimensional representative covariate information of the target population and proposes a two-step approach for variable selection and finite population inference. (via Semantic Scholar)
Sources: Crossref, ORCID
Added: January 20, 2020

2020 journal article

A Sparse Random Projection-Based Test for Overall Qualitative Treatment Effects

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 115(531), 1201–1213.

By: C. Shi n, W. Lu n & R. Song n

author keywords: High-dimensional testing; Optimal treatment regime; Precision medicine; Qualitative treatment effects; Sparse random projection
TL;DR: This article considers testing the overall qualitative treatment effects of patients’ prognostic covariates in a high-dimensional setting and proposes a sample splitting method to construct the test statistic, based on a nonparametric estimator of the contrast function. (via Semantic Scholar)
UN Sustainable Development Goal Categories
Source: Web Of Science
Added: July 29, 2019

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